code: def minmax_auto_scale(audio_arr, out_datatype):
      """
      Utility function for rescaling all audio sample values of input audio to fit the range specified
      by out_datatype.
  
      Rescaling method is min-max, which is all audio sample values are normalized to [0, 1] by using
      audio_arr.min() and audio_arr.max() and then are scaled up by certain times (eg. 255 if out_datatype is uint8).
  
      Args:
          audio_arr (numpy.ndarray): input audio ndarray.
          out_datatype (numpy.dtype): define data type as well as range after scaling. For example, np.uint8 or
                                      np.dtype('uint8'). Available options' dtype.itemsize should not greater than 4,
                                      such as uint8, int8, int16, int32, float32.
  
      Return:
          numpy.ndarray
      """
  
      _auto_scale_before(audio_arr, out_datatype)
  
      if str(out_datatype).find("int") > -1:
          output_high = np.iinfo(out_datatype).max
          output_low = np.iinfo(out_datatype).min
      else:
          output_high = np.finfo(out_datatype).max
          output_low = np.finfo(out_datatype).min
      output_type = out_datatype
  
      return rescale_intensity(
          audio_arr,
          input_low=audio_arr.min(),
          input_high=audio_arr.max(),
          output_low=output_low,
          output_high=output_high,
          output_type=output_type,
      )
  
file_path: nnabla/python/src/nnabla/utils/audio_utils/__init__.py
imports: from __future__ import absolute_import
  import numpy
  from .backend_manager import backend_manager
  from .common import rescale_intensity, _auto_scale_before
label_desc: Use image node_id 4 for calling a global function with example usage: minmax_auto_scale(audio_arr, out_datatype) and returns: rescale_intensity